This enlightening story notes that while data scientists may seem to have cool and interesting jobs, much of their work is spent on the down-and-dirty tasks of data wrangling and collection.

“[P]ractically, because of the diversity of data, you spend a lot of your time being a data janitor, before you can get to the cool, sexy things that got you into the field in the first place,” said Matt Mohebbi, a data scientist and co-founder of Iodine.

The WSJ caught up with the former data scientist for bit.ly, and she offered some skepticism on the notion of using data as a predictive tool.

“What predictive algorithms are actually really good for is still an open question,” Mason tolod the WSJ. “It was sold for a long time as they are going to know everything about you and everything you are going to do, but of course they don’t. They’re actually fairly terrible.”

Niven Narain, President and Chief Technology Officer with the pharmaceutical company Berg, argues that the biotechnology and health care industries are using archaic practices. He says a back-to-biology approach is needed.

“By listening to our own biology, our cells can take part in guiding the drug discovery process,” Narain writes. “The result? A system where the data generates the hypotheses, rather than the hypothesis blindly ‘seeing what sticks.’”

The website examined a wide range of industries and examined how they were using data to innovate. The list include Caesar’s Entertainment and its gambling rewards program and football’s Atlanta Falcons and its GPS player-tracking technology.

The Defense Advanced Research Projects Agency issued a challenged to teams to come up with a model to forecast the spread of a nasty mosquito-borne virus. The challenge is open to anyone and there is $150,000 in prize money.